Bidirectional raster scanning to increase time for vector writing in avionics see‐through displays

See‐through displays (STD) like head‐up displays (HUD) play major role in providing aircraft data to pilot through a visual interface. The data is displayed in form of symbology in pilot's line of sight using vector scanning technique and is deciphered to get flight and mission information. Contrast ratio required to see against bright sunlight at high altitudes is given only by luminance of cathode ray tube (CRT). Therefore, CRT is still used as display source in avionic HUDs, although other devices are also being explored for these applications. Aircraft's night mode operation requires raster display of external scene information along with vector data display due to low visibility during night. It reduces time available for writing vector data during night mode resulting in reduced symbology. Conventionally used raster scanning methods are unidirectional scanning methods. Bidirectional raster scanning (BRS) is an unconventional approach which scans display screen from both directions. In present work, an algorithm for BRS has been developed in VHDL providing more time for vector writing by increasing vertical retrace period (VRP) of raster scanning. Functional verification of design has been performed by simulations carried out through test‐bench and VRP is increased to 5.8304 ms from conventional 1.2800 ms per field.     

DGPose: Deep Generative Models for Human Body Analysis

International Journal of Computer Vision - Deep generative modelling for human body analysis is an emerging problem with many interesting applications. However, the latent space learned by such...     

Optimal design of 2-D FIR digital differentiator using $$L_1$$ L 1 -norm based cuckoo-search algorithm

Multidimensional Systems and Signal Processing - In this article, an optimal design of two-dimensional finite impulse response digital differentiators (2-D FIR-DD) with quadrantally odd symmetric...     

Milne, a routine for the numerical solution of Milne's problem

The routine Milne provides accurate numerical values for the classical Milne's problem of neutron transport for the planar one speed and isotropic scattering case. The solution is based on the Case eigen-function formalism. The relevant X functions are evaluated accurately by the Double Exponential quadrature. The calculated quantities are the extrapolation distance and the scalar and the angular fluxes. Also, the H function needed in astrophysical calculations is evaluated as a byproduct.

Program summary

Program title: MilneCatalogue identifier: AEGS_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGS_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 701No. of bytes in distributed program, including test data, etc.: 6845Distribution format: tar.gzProgramming language: Fortran 77Computer: PC under Linux or WindowsOperating system: Ubuntu 8.04 (Kernel version 2.6.24-16-generic), Windows-XPClassification: 4.11, 21.1, 21.2Nature of problem: The X functions are integral expressions. The convergence of these regular and Cauchy Principal Value integrals are impaired by the singularities of the integrand in the complex plane. The DE quadrature scheme tackles these singularities in a robust manner compared to the standard Gauss quadrature.Running time: The test included in the distribution takes a few seconds to run.     

Characterization and modeling of hardware imperfections in Schottky diode based six‐port modulator

This article presents digital correction for hardware imperfection in mixer‐less six‐port modulator. A passive six‐port network correlates radio frequency carrier reflected from its different ports. If the reflection coefficients at these ports are controlled by in‐phase and quadrature‐phase baseband data, the modulated information is translated directly over the radio frequency carrier without any mixing action. However, the six‐port modulator has several hardware impairments resulting into linear and nonlinear distortion. This article presents a digital characterization and distortion mitigation scheme for six‐port modulator using new quadrature interference memory polynomial model and its variant. As a proof of concept, a prototype of digitally assisted six‐port modulator is designed to modulate QAM data to radio frequency carrier at 2.0 GHz. The measurement results show the capability of modulating 16 and 64 QAM data with very low EVM less than 1.2% after employing proposed digital correction scheme.     

False topographic perception phenomena observed with the satellite images of Moon's surface

False Topographic Perception Phenomena (FTPP) are commonly observed in images of rugged terrain on the surface of the Earth acquired by polar-orbiting satellites. It is interesting to note that due to the absence of atmosphere, vegetation and presence of numerous craters on its surface, the Moon illustrates very vividly and uniquely FTPP, which is less obvious with images of the Earth. In this article images of the Moon taken during the six missions of the NASA Apollo programme and from the Chandrayan-1 Indian satellite are used to demonstrate FTPP on the surface of the Moon. Numerous craters present on the surface of the Moon are perceived as hillock/plateau and vice versa. Combinations of various interrelated factors, for example topographic relief, observer position, Sun azimuth and elevation angles, are responsible for FTPP. Craters in the northern hemisphere of the Moon exhibit FTPP as the Moon's surface was imaged from southern side under equatorial illumination.     

Validation of MODIS retrieval aerosol optical depth and an investigation of aerosol transport over Mohal in north western Indian Himalaya

This study deals with the optical properties of aerosols during 2007 over Mohal (31.9º N, 77.12º E) in north western Indian Himalaya, investigated using ground-based measurements and multi-satellite data. The daily average (mean ± standard deviation) aerosol optical depth (AOD) at 500 nm, Ångström exponent and turbidity coefficient values were 0.2 ± 0.1, 1.1 ± 0.3 and 0.1 ± 0.1, respectively. About 84% of AOD values retrieved from satellites were found to be within an uncertainty limit with a significant correlation coefficient around 0.70. The present study suggests that AOD retrieval using the Moderate Resolution Imaging Spectroradiometer (MODIS) is able to characterize AOD distribution over Mohal. However, to eliminate systematic errors, the existing MODIS algorithm needs to be modified in view of the changing aerosol optical properties, especially during the biomass-burning period. To investigate the influence of aerosol transport, a multi-sensor approach in conjunction with back-trajectory analysis was used. The observed higher values of AOD during dust-loading days with simultaneous study of the space-borne lidar measurements as well as back-trajectory analysis suggest the influx of desert aerosols. Transport of dust aerosols on 12 April, 27 April and 1 June caused a significant reduction in surface-reaching solar irradiance by 43, 40 and 39 W m^–2, respectively. Atmospheric forcing during these days increased by 33.8, 33.0 and 33.2 W m^–2, which translates into atmospheric heating rates of 0.95, 0.93 and 0.93 K day^–1, respectively. This indicates significant climatic implications due to arriving aerosols in north-western Indian Himalaya.     

Retrieval of sub-pixel snow cover information in the Himalayan region using medium and coarse resolution remote sensing data

Numerous constrained and unconstrained algorithms have been used to retrieve sub-pixel snow-cover information quantitatively using medium and coarse spatial resolution multispectral images from the Advanced Wide Field Sensor (AWiFS) and Moderate Resolution Imaging Spectrometer (MODIS) sensors over the Himalayan region. Both the methods give slow convergence rates and inaccurate estimation of sub-pixel components analysed using root mean square (RMS) error and image deviation. Multiplicative iterative algorithms such as the Expectation Maximization Maximum Likelihood Method (EMML) and the Image Space Reconstruction Algorithm (ISRA) based on the minimization of least squares and Kullback–Leibler distances have been attempted to compute the endmembers' abundances in unmixing of satellite data. In this paper we discuss the eigenvalues of minimum noise fraction (MNF) transformation bands, data noise removal using MNF transformation and selection of pure endmembers using satellite images. The normalized difference snow index (NDSI) is also estimated using field spectral reflectance results and satellite images in green and shortwave infrared (SWIR) wavelength regions in order to carry out a comparative analysis for its variations with sub-pixel snow cover fractions. The present analysis shows the advantage of iterative over direct (constrained and unconstrained) methods; constraints are easily handled and allow better regularization of the solution for the ill-conditioned cases. Iterative methods are found to be faster compared to those of direct methods and can be used operationally for all resolution data for accurate estimation of sub-pixel snow cover.     

Transductive methods for the distributed ensemble classification problem

We consider ensemble classification for the case where there is no common labeled training data for jointly designing the individual classifiers and the function that aggregates their decisions. This problem, which we call distributed ensemble classification, applies when individual classifiers operate (perhaps remotely) on different sensing modalities and when combining proprietary or legacy classifiers. The conventional wisdom in this case is to apply fixed rules of combination such as voting methods or rules for aggregating probabilities. Alternatively, we take a transductive approach, optimizing the combining rule for an objective function measured on the unlabeled batch of test data. We propose maximum likelihood (ML) objectives that are shown to yield well-known forms of probabilistic aggregation, albeit with iterative, expectation-maximization-based adjustment to account for mismatch between class priors used by individual classifiers and those reflected in the new data batch. These methods are extensions, for the ensemble case, of the work of Saerens, Latinne, and Decaestecker (2002). We also propose an information-theoretic method that generally outperforms the ML methods, better handles classifier redundancies, and addresses some scenarios where the ML methods are not applicable. This method also well handles the case of missing classes in the test batch. On UC Irvine benchmark data, all our methods give improvements in classification accuracy over the use of fixed rules when there is prior mismatch.     

Synthesis of C60 Fullerene-Silica Hybrid Nano Structures

We have recently demonstrated a procedure for the synthesis of silica nanometer and micrometer particles under modest conditions. Here we report the synthesis of C₆₀ fullerene-silica hybrid nanometer sized materials via sol-gel processing at neutral pH and under ambient conditions. The C₆₀ fullerene, when functionalized, was water-soluble and also able to facilitate the formation of silica structures from an aqueous silica precursor. This C₆₀ fullerene had similar functionality to the cationically charged polymers, which have been reported earlier to act as catalysts/templates for silicification. The resulting organic-inorganic hybrid was studied using SEM, EDS and UV/Vis spectroscopy. These hybrid materials may have applications in areas such as optical devices, semiconductors, chemical sensors, catalysis and in the medical field. The results presented in this study may be useful in developing a process for the synthesis of novel organic-inorganic nanometer sized materials and for the biomimetic synthesis of silica.